Evidence map›Paper›PMID 27357693›Full record

ArticleBMC genomics2016

VarElect: the phenotype-based variation prioritizer of the GeneCards Suite.

Gil Stelzer, Inbar Plaschkes, Danit Oz-Levi, Anna Alkelai, Tsviya Olender, Shahar Zimmerman, Michal Twik, Frida Belinky, Simon Fishilevich, Ron Nudel and 11 more

Abstract read
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 157 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
157citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

157 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. PhenoSS: phenotype semantic similarity-based approach for rare disease prediction and patient clustering.Journal of the American Medical Informatics Association : JAMIA · 2026
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  11. X-Linked Muscular Dystrophy in a Cat with a Putative Variant in theAnimals : an open access journal from MDPI · 2026
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  20. Network-Based Identification ofCurrent pharmaceutical design · 2026
    Article

97 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Gil StelzerDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
Inbar PlaschkesLifeMap Sciences Ltd, Tel Aviv, Israel.
Danit Oz-LeviDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
Anna AlkelaiDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
Tsviya OlenderDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
Shahar ZimmermanDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
Michal TwikDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
Frida BelinkyNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
Simon FishilevichDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
Ron NudelDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
Yaron Guan-GolanLifeMap Sciences Inc, Marshfield, MA, 02050, USA.
David WarshawskyLifeMap Sciences Inc, Marshfield, MA, 02050, USA.
Dvir DaharyLifeMap Sciences Ltd, Tel Aviv, Israel.
Asher KohnLifeMap Sciences Inc, Marshfield, MA, 02050, USA.
Yaron MazorLifeMap Sciences Ltd, Tel Aviv, Israel.
Sergey KaplanLifeMap Sciences Ltd, Tel Aviv, Israel.
Tsippi Iny SteinDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
Hagit N BarisThe Genetics Institute, Rambam Health Care Campus, Haifa, Israel.
Noa RappaportDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
Marilyn SafranDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
Doron LancetDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel. doron.lancet@weizmann.ac.il.

Funding

Nomenclature of Human and Vertebrate GenesU41HG003345 · NHGRI · EUROPEAN MOLECULAR BIOLOGY LABORATORY · PI BIRNEY, EWAN, BRUFORD, ELSPETH · 2013 to 2017
$2.4M
NHGRI NIH HHS U41 HG003345
6 · The paper itself

Abstract

backgroundNext generation sequencing (NGS) provides a key technology for deciphering the genetic underpinnings of human diseases. Typical NGS analyses of a patient depict tens of thousands non-reference coding variants, but only one or very few are expected to be significant for the relevant disorder. In a filtering stage, one employs family segregation, rarity in the population, predicted protein impact and evolutionary conservation as a means for shortening the variation list. However, narrowing down further towards culprit disease genes usually entails laborious seeking of gene-phenotype relationships, consulting numerous separate databases. Thus, a major challenge is to transition from the few hundred shortlisted genes to the most viable disease-causing candidates.

resultsWe describe a novel tool, VarElect ( http://ve.genecards.org ), a comprehensive phenotype-dependent variant/gene prioritizer, based on the widely-used GeneCards, which helps rapidly identify causal mutations with extensive evidence. The GeneCards suite offers an effective and speedy alternative, whereby >120 gene-centric automatically-mined data sources are jointly available for the task. VarElect cashes on this wealth of information, as well as on GeneCards' powerful free-text Boolean search and scoring capabilities, proficiently matching variant-containing genes to submitted disease/symptom keywords. The tool also leverages the rich disease and pathway information of MalaCards, the human disease database, and PathCards, the unified pathway (SuperPaths) database, both within the GeneCards Suite. The VarElect algorithm infers direct as well as indirect links between genes and phenotypes, the latter benefitting from GeneCards' diverse gene-to-gene data links in GenesLikeMe. Finally, our tool offers an extensive gene-phenotype evidence portrayal ("MiniCards") and hyperlinks to the parent databases.

conclusionsWe demonstrate that VarElect compares favorably with several often-used NGS phenotyping tools, thus providing a robust facility for ranking genes, pointing out their likelihood to be related to a patient's disease. VarElect's capacity to automatically process numerous NGS cases, either in stand-alone format or in VCF-analyzer mode (TGex and VarAnnot), is indispensable for emerging clinical projects that involve thousands of whole exome/genome NGS analyses.

Indexed as

AlgorithmsComputational BiologyDatabases, GeneticData MiningGenome, HumanHigh-Throughput Nucleotide SequencingHumansPhenotypeGene prioritizationGuilt by associationNext generation sequencing analysisPhenotype interpretationPhenotypingVariant selection

Identifiers

PMID27357693
PMCPMC4928145

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.